- Multiple|instance learning for text categorization based on semantic ...🔍
- multiple|instance learning for text categorization based on semantic ...🔍
- Multi|dimensional Semantic|based Text Classification Model🔍
- A Text Classification Model via Multi|Level Semantic Features🔍
- Review of Multi|Instance Learning and Its applications🔍
- Multi|Class Text Classification Model Comparison and Selection🔍
- Text|based image retrieval using progressive multi|instance learning🔍
- Multiple instance classification🔍
Multiple|instance learning for text categorization based on semantic ...
Multiple-instance learning for text categorization based on semantic ...
Complex semantic information can influence the precision of text categorization. In this paper, we propose a new method to handle the semantic correlations ...
multiple-instance learning for text categorization based on semantic ...
2010 Mathematics Subject Classification. 97R40. Key words and phrases. Text categorization, text representation, Multiple-Instance learning, mi-SVM ...
Multiple-instance learning for text categorization based on semantic ...
Multiple-instance learning for text categorization based on semantic representation. Jian-Bing Zhang , ,; Yi-Xin Sun ,; De-Chuan Zhan. National Key Laboratory ...
Multiple-instance learning for text categorization based on semantic ...
A new method to handle the semantic correlations between different words and text features from the representations and the learning schemes is proposed and ...
Multiple-instance learning for text categorization based on semantic ...
Multiple-instance learning for text categorization based on semantic representation ... To read the full-text of this research, you can request a copy directly ...
Multi-dimensional Semantic-based Text Classification Model
Multi-dimensional Semantic-based Text Classification Model ... Abstract: In recent years, many excellent text classification models have been proposed by ...
A Text Classification Model via Multi-Level Semantic Features - MDPI
In summary, we present a text classification model based on multi-level semantic features to achieve a high accuracy rate while having small model size and few ...
Review of Multi-Instance Learning and Its applications
(2002) applied SVM-based MIL methods to the problem of text categorization, where each document is represented by overlapping passages consisting of 50 words in ...
Multi-Class Text Classification Model Comparison and Selection
Multi-Class Text Classification Model Comparison and Selection · The Data · Exploring the Data · Text Pre-processing · Naive Bayes Classifier for Multinomial Models.
Text-based image retrieval using progressive multi-instance learning
This work proposes a new approach to learn a robust classifier for text-based image retrieval (TBIR) using relevant and irrelevant training web images, ...
Multiple instance classification: Review, taxonomy and comparative ...
In the Multiple Instance Learning (MIL) task we learn a classifier based on a training set of bags, where each bag contains multiple feature vectors (called ...
Machine learning in automated text categorization
In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a ...
A Semantic-Based Framework for Multi-Label Text Classification
In the field of natural language processing (NLP), the objective of multi-label text categorization (MLTC) is exceedingly challenging.
Semantic Ontology-Based Approach to Enhance Text Classification
The machine learning based classifiers that can be used for text classification are: ... After this computation we can compare the performance of multiple ...
Learning Semantic Similarity for Multi-label Text Categorization
To address this problem, we learn the word semantic similarity by deep learning using the unlabelled text data, and then incorporate the learned word semantic ...
Text Representation and Classification Based on Multi-Instance ...
The text classification problem is translated into multi-instance learning problem. In order to solve this problem, a Chinese text classifier focusing on bag ...
A deep multiple-instance text binary classification for topic relevant ...
The proposed method introduces latent variables, Bernoulli distribution, and variational inference into multiple-instance learning (MIL) to generate pseudo ...
Semantic-Unit-Based Dilated Convolution for Multi-Label Text ...
We propose a novel model for multi-label text classification, which is based on sequence- to-sequence learning. The model gener- ates higher-level semantic ...
A Comprehensive Review on Multiple Instance Learning
In other words, when training instances have known labels, and there is consequently the least amount of ambiguity, supervised learning datasets are based on ...
learning a function f : X × C → [0,1], where. X denotes a text-based instance space and C a set of class descriptions. Here f maps (example, class ...